Abstract
As trust-based data and message security is reliable and efficient in the case of resource and power constraints networks, it finds a new field of research for researchers in wireless sensor networks. Till now, a lot of researches have been carried out to set up trust management systems in the above network. Probability distribution functions have a great role in the calculation of trust and reputation. In this paper, we have introduced a trust model based on clustered routing scheme. Probability distribution functions and metaheuristic algorithms have been used in the calculation of trust values. By using MATLAB tool, our work has been compared with ECSO algorithm, which is one of the latest efficient trust scheme in WSNs and obtained much efficient results. We have experimented taking into consideration of small networks consisting of 50 and 100 sensor nodes and can claim to have the latest efficient trust model to be used for enhancing the security of small-scale WSNs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Xiang, G., Jianlin, Q., Jin, W.: Research on trust model of sensor nodes in WSNs. Procedia Eng. 909–913 (2012)
Buchegger, S., Boudec, J.Y.L.: Performance analysis of the CONFIDANT protocol (Cooperation Of Nodes—Fairness In Dynamic Ad-hoc NeTworks). In: The 3rd ACM International Symposium Mobile Ad-hoc Networking & Computing (MobiHoc’02), Lausanne, CH (2002)
Michiardi, P., Molva, R.: CORE: a collaborative reputation mechanism to enforce node cooperation in mobile ad-hoc networks. In: The IFIP TC6/TC11 Sixth Joint Working Conference on Communications and Multimedia Security: Advanced Communications and Multimedia Security, Portoroz, Slovenia (2002)
Wu, X., Huang, J., Ling, J., Shu, L.: BLTM: beta and LQI based trust model for wireless sensor networks. IEEE Access 7 (2019). https://doi.org/10.1109/access.2019.2905550
Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the Hawaii International Conference on System Sciences, Maui, Hawaii, 4–7 Jan 2000
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wireless Commun. 1(4), 660–670 (2002)
Wu, W., Xiong, N., Wu, C.: Improved clustering algorithm based on energy consumption in wireless sensor networks. In: IET Networks. The Institution of Engineering and Technology (2017)
Liu, J.L., Ravishankar, C.V.: LEACH-GA: genetic algorithm-based energy efficient adaptive clustering protocol for wireless sensor networks. Int. J. Mach. Learn. Comput. 1(1), 79–85 (2011)
Sivakumar, P., Radhika, M.: Performance analysis of LEACH-GA over LEACH and LEACH-C in WSN. Procedia Comput. Sci. 125, 248–256 (2018)
Zhao, L., Qu, S., Yi, Y.: A modified cluster-head selection algorithm in wireless sensor networks based on LEACH. EURASIP J. Wireless Commun. Netw. 2018, 287 (2018)
Kulkarni, P.K.H., Jesudason, P.M.: Multipath data transmission in WSN using exponential cat swarm and fuzzy optimisation. IET Commun. 13(11), 1685–1695 (2019). https://doi.org/10.1049/iet-com.2018.5708
Youdao, Y., Wagan, R.A., Bukhari, A.H.S.: Parametric identification for fractional order model based on hybrid artificial bee colony algorithm. In: 5th International Conference on Computer Science and Network Technology (ICCSNT), Changchun, China, pp. 401–406 (2016)
Valdez, F., Vazquez, J.C., Gaxiola, F.: Fuzzy dynamic parameter adaptation in ACO and PSO for designing fuzzy controllers: the cases of water level and temperature control. Adv. Fuzzy Syst. 19. Article ID 1274969 (2018)
Hindriks, K.V., Hoogendoorn, M., Goebel, R.: Penguins search optimization algorithm (PeSOA) in applied artificial (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Panigrahi, L., Jena, D. (2021). Genetic Algorithm and Probability-Based Leach Variant Trust Management Model for WSNs. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol 194. Springer, Singapore. https://doi.org/10.1007/978-981-15-5971-6_71
Download citation
DOI: https://doi.org/10.1007/978-981-15-5971-6_71
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5970-9
Online ISBN: 978-981-15-5971-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)